Population Health: Five Important Questions to Ask When Integrating Your Data

Population health has become a puzzle of processes and technologies to improve health outcomes, enhance the physician-patient experience, and reduce costs. Although the healthcare industry is making great strides toward achieving these goals, a necessary step—the integration of clinical, claims and wellness data—has just begun.

Today, many medical business decisions are based on claims data; yet, robust insights into clinical quality require clinical data. Furthermore, information that is not typically found in healthcare information systems, such as that from wearable devices, and from those who may have little to no contact with the health care system, needs to be incorporated into population health management systems.

Accessibility to clinical, claims and wellness data can provide physicians and care teams with a more complete view of the care delivery system journey and an integrated view of a patient’s data as he or she has engaged the healthcare system. With a broader view of a population’s health and various opportunities to proactively address an individual’s care, a physician or care team can help prevent adverse events or future disease to ultimately improve the health and well-being of the individuals they serve.

As we embark on this journey to complete the population health puzzle, it is important that healthcare systems, physicians and care teams optimize the value of integrating clinical, claims and wellness data by considering the five questions I have outlined below.

Do you have a reliable, complete and manageable way to access clinical, claims and wellness data?

Clinical data, in its current state, requires an “interoperable platform” to be able to present a single, comprehensive view of a patient’s or population’s health data at the point of care. An interoperable platform connects disparate electronic health record (EHR) systems across a community to collect and provide access to information in a secure and confidential way.

Claims data, traditionally aggregated from health insurers, and now from Accountable Care Organizations, needs to be integrated as well to create a more complete picture of an individual’s or population’s health. Not only does claims data yield rich insights that may not be present in clinical information alone—for example, completed pharmacy transactions—but it can also display health-related activity that occurs outside of any given health system. This could pertain to the use of a non-network urgent care facility or activity that might not be captured in an EHR, such as retail pharmacy vaccinations.

Wellness data generated from things such as immunization campaigns, wellness fairs or wearable health technologies, which seem to be on the rise, can help provide a broader record of an individual’s health so that a physician or care team does not have to rely only on sick encounters. Wellness data can help physicians and care teams identify opportunities in the course of an individual’s health, to intervene earlier and try to prevent some of the complications, or even some of the illnesses, from occurring in the first place.

Therefore, ensuring all of this valuable health information is accounted for to generate a more complete picture of a given patient’s or population’s health, requires accessibility to the data, achieved through community-wide interoperability, and a thoughtful plan for using the data to drive quality improvement, care experience enhancements, and reduced health care costs and utilization—the “Triple Aim.”

Do you have a way to normalize your data and corroborate your inferences?

Transitioning from data access to achieving the Triple Aim requires that clinical, claims and wellness data make sense together, across various systems and coding schema. In other words, the data must be normalized, duplicate and time-decayed information removed, and data gaps filled in by interpretation or clinical corroboration with other information.

Normalization requires a platform and an approach that first recognizes that clinical, claims and wellness data may conflict or overlap, and provides a systematic way to address these issues. This all requires solid quality assurance activities, software, and staff with sufficient data science skills to be able to bring clinical, claims, and wellness data together and use the integrated data set to provide actionable health intelligence.

Additionally, as standards are becoming more broadly adopted and health systems are becoming more sophisticated in their use of information technology, data normalization will become more seamless. Until then, I believe it will remain a critical issue.

Do you have an analytics approach that is both powerful and flexible enough to take advantage of the combined data?

A strong analytics approach that can make sense of standardized information within a combined database of clinical, claims and wellness data is key. Simply trying to apply claims-based analytics to a richer database of information will not provide the type of actionable insights ultimately gained from a combined data set. Furthermore, clinicians and other end-users of the analytics output are more likely to take action on information that is derived from transparent data sources. Therefore, it is crucial that analytics are run on all of the data types available and that the information is presented in a way that is transparent and credible to end users.

How are you going to present the data?

Often times, good information is not presented in a way that the end user, or the individual who is supposed to take action on the information, can understand, or the information is presented in a way that inhibits the end user’s trust in the data. Therefore, the presentation of clinical, claims and wellness data must be sensitive to a physician’s or care team’s workflow. Additionally, if you are asking a physician to pivot from a paper-based to electronically based environment, asking him or her to deal with the combined analytics output may incur challenges that reduce the impact of this combined data.

Physicians are typically trained to trust only the data that they have entered or that they have a clear view to. As a result, many physicians are reluctant to adopt or take action on information that comes from claims data alone, even if the information is clinically relevant and correct. In part, this is because of a lack of familiarity with the richness of clinical content found in claims data, and to some extent, the inelegant presentation of claims data often provided to physicians.

Therefore, it is critical that clinical, claims and wellness data are not only reliable, but presented in a way that can be trusted by a physician. It must provide a degree of transparency, so that the physician can see where the information came from and can feel comfortable and confident in its relevance to the patient under the physician’s care.

How are you going to measure the impact and effectiveness of your analytics approach and data presentation?

To ensure the successful adoption of analytics output from integrating clinical, claims and wellness data, it is critical to have a way of measuring the impact and effectiveness of this combined data set. Success can be measured by who is using the data; how it is being used; or any improvements in care quality or changes in a patient’s behavior as a result of—or at least temporally related to—the initiation of integrated data tools. The success measures should be quantified and sent back into the system so that continuous improvement in data and analytics quality, relevance and usefulness can occur.

In addition, it is important to determine how clinical, claims and wellness data are helping a practice. This includes a wide array of quality measures to determine a clinic’s performance from a financial and clinical perspective, the physician adoption rate of the technology, and a patient’s health outcomes. For example, a study conducted by the Journal of the American Board of Family Medicine demonstrated that a vaccination reminder system within a physician’s EHR can significantly improve vaccination series initiation and completion. The return on the investment made in the data collection, analytics and presentation to physicians was, in this study, measured and reported. Measuring and reporting improvements from data and analytics can spur adoption and additional investment in population health management.

Clearly, there is no shortage of challenges to overcome while integrating clinical, claims and wellness data. However, I believe the five questions outlined above will help provide a framework for how to begin thinking about the transition from data silos to a more complete and longitudinal view of a patient or population. An organization, physician, or care team that can answer these five questions is well on its way toward completing the population health puzzle and realizing the benefits of an approach that ultimately improves the health and well-being of the individuals served.